First Innovate for Ireland National Centre launched – ‘Decarb-AI’

The first Innovate for Ireland national centre, ‘Decarb-AI: AI-Powered Pathways to Climate Resilience’ has been announced today. Created in partnership with AIB and Research Ireland, the €5.7m Decarb-AI national centre will aim to harness the power of artificial intelligence (AI) to accelerate Ireland’s transition to a climate-resilient, low-carbon future.

Decarb-AI will welcome 30 iScholars across three intakes. Eight iScholars – from China, Ghana, India, UK, France, Ireland and Kenya – have already commenced their research. All of these iScholars will undertake fully-funded, four-year PhDs under the supervision of leading academic researchers from Irish higher education  institutions, which are:  University College Dublin (lead institution), Trinity College Dublin, Dublin City University, Technological University Dublin, University of Limerick, University of Galway (via the Irish Centre for High-End Computing – ICHEC), and University College Cork. The iScholars’ research at Decarb-AI research centre will focus on using cutting-edge AI to advance climate mitigation and adaptation across Ireland, with key focus areas including:

  • AI-optimised renewable energy systems and datacentre sustainability
  • Machine learning for water quality forecasting and peatland restoration
  • Earth-observation and biodiversity modelling for land-use policy
  • AI-supported sustainable finance tools for SMEs
  • Transparent AI decision-support systems for real-time decarbonisation planning

The launch of Decarb-AI is a major milestone for the Innovate for Ireland programme. It follows on from the programme’s successful launch in early 2025, which saw the recruitment of the first cohort of 11 iScholars working in a variety of research disciplines. iScholars are outstanding researchers with entrepreneurial qualities and a passion for sustainability.

Yvonne McCarthy , Head of Sustainability Research, AIB, commented: “Tackling climate change requires both ambition and innovation. AIB is proud to partner with Innovate for Ireland on Decarb-AI, an initiative that brings world-leading researchers together to accelerate Ireland’s transition to a low-carbon economy. By supporting the development of AI-driven tools for energy and sustainable finance, we’re helping to unlock some of the solutions that will ensure that businesses and communities can make meaningful progress on decarbonisation that allows them to thrive.”

Dr Diarmuid O’Brien, CEO Research Ireland, commented: “By combining advanced AI research with real-world climate challenges, Decarb-AI has the potential to generate solutions that are both scientifically rigorous and nationally impactful. This initiative will train the next generation of interdisciplinary leaders and strengthen Ireland’s credentials in climate research innovation.”

Andrew Parnell, Lead PI and Professor of Data Science for Weather and Climate at University College Dublin, commented “AI is the catalyst required to solve the multi-objective problems inherent in climate resilience. Through Decarb-AI, we are fostering a research environment where advanced data science meets urgent environmental necessity through our new iScholars. Our focus is on creating scalable, academically rigorous, and industry-ready outputs ranging from peatland restoration to sustainable finance. We must ensure that Ireland remains at the global forefront of excellence in AI and sustainability.”

Dr Simon Boucher, Chief Executive, Global Innovators Ireland, commented: “The opening of the Decarb-AI national centre is an important step towards realising the Innovate for Ireland vision of establishing Ireland as a world-leading hub for sustainability innovation and helping to address the world’s most pressing challenges.”

Applications for a second cohort of researchers to Decarb-AI will be invited from ambitious candidates with backgrounds in AI, data science, engineering, environmental science, ecology, geography, finance, and related fields who want to build high-impact AI solutions for climate resilience.

Top 7 Data Visualization and Tableau Courses to Build Analytical Leadership Skills in 2026

According to a 2026 report by Mordor Intelligence, the Business Intelligence market adoption has hit 82%, yet a severe training gap remains. 

Research from BCG indicates that 70% of digital transformations fail due to poor data literacy and visualization. 

In this article, you will discover the top data visualization courses designed to bridge that gap and drive real analytical leadership.

How Have We Selected These Best Tableau & Power BI Training Courses?

  • Curriculum relevance to the 2026 data-driven corporate ecosystem.
  • Institutional prestige & the professional caliber of the certifying body.
  • Focus on analytical architecture (e.g., Power Query, DAX, AI Copilot integration) rather than mere data entry.
  • Flexibility of delivery modes suited for high-level executive schedules.
  • Direct applicability of outcomes to enterprise-scale problem-solving & financial modeling.

Overview: Best Tableau & Power BI Courses for 2026

# Program Provider Primary Focus Delivery Ideal For
1 Advanced Data Viz (Power BI) Great Learning Executive Dashboarding Online/Self-Paced Senior Leaders
2 Data Analysis & Viz (Power BI) Coursera (MS) Technical Modeling Online/Self-Paced Career Switchers
3 Data Visualization in Power BI DataCamp Interactive Exploration In-Browser Hands-on Managers
4 Tableau Essentials Great Learning Visual Storytelling Online/Self-Paced Technical VPs
5 Power BI (PL-300) ONLC Certification & Governance Live Virtual Compliance Officers
6 Power BI for Data Analysis Data for Dev Humanitarian Impact Online Workshop Non-Profit Leaders
7 Power BI Nanodegree Udacity Project-Based Mastery Online/Mentored C-Suite Finance

Best Power BI Training and Tableau Courses in 2026

1. Advanced Data Visualization using Power BI — Great Learning

This Power BI Training course by Great Learning is designed for professionals who need to go beyond basic reporting to build robust, executive-level data pipelines. 

 

It provides an in-depth dive into hierarchical charts, clustering, and complex What-If analyses. 

 

Enrolling in this GLA Pro+, learners gain access to 500+ courses, AI-powered career tools, guided projects, and recognized certifications from Microsoft and AWS to strengthen their career prospects.

 By the end of this course, leaders can extract actionable insights from real-world business scenarios.

 

  • Delivery & Duration: Online, 11 hours, self-paced with 1 major guided project (FIFA Player Analysis).
  • Credentials: Certificate of completion (Great Learning and Microsoft recognized).
  • Instructional Quality & Design: Faculty-led video modules featuring enterprise case studies and interactive labs.
  • Support: 24-hour AI assistance, AI resume builder, and personalized mock interviews.

 

Key Outcomes / Strengths:

  • Architect data modeling workflows utilizing advanced visualizations and cross-filtering.
  • Formulate dynamic parameters to execute high-stakes What-If scenario analyses.
  • Synthesize complex datasets through clustering to identify market outliers.
  • Evaluate operational bottlenecks through interactive dashboards to drive profitability.

2. Data Analysis and Visualization with Power BI — Coursera

Developed directly by Microsoft, this program focuses on the technical end-to-end process of preparing and modeling data. 

 

It is the gold standard for those seeking a software-authorized path to the PL-300 certification. 

 

The curriculum emphasizes data cleaning with Power Query and the implementation of scalable relational models.

 

  • Delivery & Duration: Online, flexible schedule; approximately 30 hours of instructional material.
  • Credentials: Shareable Professional Certificate from Microsoft and Coursera.
  • Instructional Quality & Design: Video lectures from Microsoft experts combined with hands-on labs.
  • Support: Peer discussion forums and automated grading with instant technical feedback.

 

Key Outcomes / Strengths:

  • Deconstruct enterprise databases into functional datasets using Power Query.
  • Implement robust dimensional data models using star schemas for reporting accuracy.
  • Translate business requirements into clear visual narratives using advanced features.
  • Apply best practices in data governance within the Power BI Service environment.

3. Data Visualization in Power BI — DataCamp

This interactive course serves as a strategic entry point for managers who value efficiency.

 

 It utilizes an in-browser sandbox to teach the essentials of data visualization software, requiring no local installation. 

 

The focus is on rapid drag-and-drop dashboarding and immediate data exploration.

 

  • Delivery & Duration: Online interactive platform; 6 hours of modular, skill-focused learning.
  • Credentials: Statement of Accomplishment upon track completion.
  • Instructional Quality & Design: 60 interactive exercises offering immediate coding and design feedback.
  • Support: Community-led help center and downloadable coding cheatsheets.

 

Key Outcomes / Strengths:

  • Navigate the Power BI interface to connect to local and cloud-based datasets.
  • Construct foundational visualizations, including interactive bar charts and geographic maps.
  • Evaluate sorting and filtering techniques to drill down into specific data points.
  • Implement basic DAX measures to calculate essential performance indicators.

4. Tableau Data Visualization Essentials — Great Learning

This Tableau course by Great Learning helps professionals move past spreadsheets to build robust, executive-level data stories. 

 

It provides an in-depth dive into visual analytics, data structuring, and parameterized reporting. The focus is on “visual logic,” ensuring that dashboards solve specific business problems rather than just presenting raw numbers.

 

Enrolling in this GLA Pro+, learners gain access to 500+ courses, AI-powered career tools, guided projects, and recognized certifications from Microsoft and AWS to strengthen their career prospects.

  • Delivery & Duration: Online, 8 hours of video content with 1 major guided project.
  • Credentials: Verified Certificate of Completion in Tableau.
  • Instructional Quality & Design: Faculty-led modules focusing on storytelling and dashboard blueprinting.
  • Support: Access to a network of 5 million+ learners and dedicated AI mentorship.

 

Key Outcomes / Strengths:

  • Architect dynamic dashboards utilizing heat maps, tree maps, and Pareto charts.
  • Formulate complex calculations and parameters to allow end-user interaction.
  • Synthesize clear data-driven stories using Tableau’s unique storyboarding features.
  • Apply data blending techniques to merge disparate sources into a unified visual truth.

5. Microsoft Power BI Data Analyst (PL-300) — ONLC

For professionals focused on corporate compliance and official standards, this program offers an exam-aligned curriculum. 

 

It emphasizes the governance and administrative aspects of a Power BI deployment. It is specifically tailored for those who will oversee an organization’s entire BI infrastructure and security protocols.

 

  • Delivery & Duration: Live virtual classes (4 days) or self-paced on-demand options.
  • Credentials: Prepares students for the Microsoft PL-300 certification exam.
  • Instructional Quality & Design: Instructor-led labs that replicate real-world enterprise IT environments.
  • Support: Direct interaction with certified instructors and post-training resources.

 

Key Outcomes / Strengths:

  • Architect secure data environments by applying Role Level Security (RLS).
  • Manage the full lifecycle of a report from initial query to final publication.
  • Optimize report performance by identifying bottlenecks in the data model.
  • Standardize metric definitions across the organization using shared datasets.

6. Power BI for Data Analysis Workshop — Data for Dev

This specialized workshop is ideal for leaders in the non-profit sector. It frames Power BI within the context of monitoring, evaluation, and impact reporting. 

 

The course focuses on using data to tell a compelling story to donors and stakeholders, using humanitarian-specific datasets.

 

  • Delivery & Duration: Online workshop; 10 hours of intensive, project-focused training.
  • Credentials: Certificate of Participation in Data Analysis for Development.
  • Instructional Quality & Design: Case-study driven learning using real humanitarian datasets.
  • Support: Access to a peer community of development professionals.

 

Key Outcomes / Strengths:

  • Build specialized impact dashboards that track project indicators and donor requirements.
  • Automate the cleaning of multi-source field data for immediate visual analysis.
  • Formulate interactive maps to visualize project reach and resource distribution.
  • Cultivate transparent data environments that facilitate trust with global stakeholders.

7. Data Analysis and Visualization with Power BI — Udacity

The Udacity Nanodegree offers an intensive, real-world analytical blueprint for professionals seeking mastery. 

 

It moves from basic navigation to complex DAX iterators and time-intelligence functions. It is the most comprehensive option for those seeking a deep career pivot into professional data engineering or C-suite analytics.

 

  • Delivery & Duration: Online; approximately 4 months at 10 hours per week; mentored.
  • Credentials: Professional Nanodegree Certificate.
  • Instructional Quality & Design: Project-centric curriculum reviewed by human experts for industry-grade quality.
  • Support: Technical mentor support, career coaching, and portfolio reviews.

 

Key Outcomes / Strengths:

  • Synthesize advanced relational data models (Star and Snowflake schemas).
  • Build dynamic time-intelligence tools and apply complex DAX measures.
  • Design custom scenario analyses utilizing advanced conditional formatting.
  • Execute professional-grade data storytelling that bridges the gap for C-suite decisions.

Conclusion

In 2026, the distinction between a “manager” and a “data analyst” is rapidly disappearing. The ability to command data visualization tools at an advanced level is no longer just about generating simple charts; it is about engineering the architecture of business intelligence. 

 

Selecting the right online free courses with certificate today is the most significant step toward mastering data visualization and analytical leadership in 2026.

 

How Xero and Sage Support Making Tax Digital Compliance

Choosing accounting software is one of the first practical decisions any UK business faces when preparing for Making Tax Digital. The platform you select shapes how you store records, calculate VAT, and submit returns to HMRC. Two names come up consistently in this conversation: Xero and Sage. Both carry HMRC recognition. Both handle the technical requirements. But they approach the job differently, and understanding those differences is what makes the choice useful rather than arbitrary.

The Baseline: What MTD Demands from Any Software

MTD sets specific technical requirements that software must meet to qualify as compliant.

Your platform must store digital records of all income and expenses. It must calculate VAT automatically from those records. It must generate returns in the format HMRC accepts and transmit them directly via API — not through a manual export or copy-paste process. And it must maintain a complete digital audit trail linking every figure in your return back to the original transaction.

That last point is where many businesses unknowingly fall short. If your process involves transferring numbers from one system into another by hand at any stage, you’ve broken the digital link requirement. The software may be HMRC-approved; the way you’re using it may not be compliant.

Xero and Sage both satisfy these requirements in full. Where they differ is in design philosophy, workflow, and the types of businesses they serve most effectively.

Xero’s Approach to MTD

Xero operates entirely in the cloud. There’s no software to install, no server to maintain, and no files to transfer between devices. You log in through a browser or mobile app, and your data is available in real time to anyone you authorise — including your accountant.

The platform’s MTD-relevant strengths centre on automation. Bank feeds connect directly to your business accounts and pull transactions into Xero automatically. The mobile app lets you photograph receipts and attach them to transactions on the spot. VAT returns are generated from your categorised records with minimal manual input, then submitted to HMRC directly from within the platform.

Xero suits businesses that want to keep day-to-day bookkeeping straightforward. A sole trader, a small consultancy, or a growing e-commerce business will typically find the interface intuitive and the setup manageable without specialist finance knowledge. The accountant collaboration model also works well here — shared access means your adviser can review, adjust, and submit without requiring files to be exported and emailed back and forth.

Sage’s Approach to MTD

Sage has a longer history in UK accounting than most of its competitors, and its user base reflects that. Many established businesses have used Sage products for years, some running operations on Sage 50 or earlier desktop versions.

The modern Sage cloud platform carries forward the structural depth that made those earlier versions popular. Detailed financial ledgers, departmental cost tracking, customisable reporting, and support for multiple VAT schemes give finance teams the granular control they need for complex operations. For businesses processing high transaction volumes or managing accounts across multiple cost centres, that structure is a practical necessity rather than an optional feature.

Sage also offers a defined migration path for businesses moving from legacy desktop versions. Maintaining continuity of financial history — opening balances, VAT records, chart of accounts — matters significantly for businesses with years of data in an existing Sage system. Switching to an entirely new platform means solving a data migration problem that Sage’s own upgrade path avoids.

Matching the Platform to the Business

Neither platform is universally better. The relevant question is which one fits how your business actually operates.

Smaller businesses and sole traders tend to favour Xero. The learning curve is lower, the interface requires less accounting knowledge to navigate, and the automation features reduce the time spent on routine bookkeeping. For businesses without a dedicated finance function, that matters.

Larger businesses and those with internal finance teams often find Sage more capable. Departmental tracking, detailed ledger management, and robust reporting customisation give accountants and finance managers tools they can’t replicate in a simpler platform. Businesses in manufacturing, construction, or other sectors with job costing requirements particularly benefit from Sage’s feature depth.

Transaction volume is another practical consideration. A business processing a handful of invoices per week has different software needs than one handling hundreds of purchase orders and supplier payments daily. Sage’s ledger architecture scales more naturally for the latter.

Both platforms require correct configuration to work as MTD-compliant systems, and that’s where many businesses encounter problems. Selecting the software is straightforward; setting it up correctly is where the detail lies. Services like Xero, QuickBooks & Sage MTD Setup provide structured implementation support, ensuring the platform you choose is configured accurately for HMRC submissions before your first return is due.

What Correct Configuration Actually Involves

Installing software and creating a login is not the same as being MTD-compliant. The configuration work that happens between those two points determines whether your submissions are accurate and whether your records meet HMRC’s digital link requirements.

The VAT scheme selection is one of the most consequential settings. Standard VAT accounting, Cash Accounting, and the Flat Rate Scheme each calculate liability differently. Applying the wrong scheme means every VAT return you produce carries a systematic error — one that may not surface until an HMRC review.

The chart of accounts needs to reflect how your business actually operates, with income and expense categories mapped correctly to the relevant tax treatment. Poorly structured nominal codes produce returns that misrepresent your VAT position, regardless of how carefully you record individual transactions.

The HMRC API connection must be established, authorised, and tested before you file your first return. Bank feeds need to be verified against your actual accounts. For businesses migrating from older systems, historical data must transfer with opening balances and VAT history intact.

Errors at this stage tend to compound. A misconfigured VAT scheme or a misaligned chart of accounts produces incorrect returns quarter after quarter until someone identifies and corrects the underlying problem.

Sustaining Compliance After Implementation

Software configuration is a one-time project, but staying compliant is ongoing. Both Xero and Sage require users who understand how to operate them correctly — logging expenses accurately, reconciling bank feeds regularly, reviewing VAT before submission, and maintaining the categorisation discipline that makes quarterly returns reliable.

Structured onboarding training, tailored to how your business uses the platform, reduces the errors that stem from unfamiliarity. Some businesses also benefit from periodic compliance reviews — a check that records are reconciled, VAT coding is consistent, and the submission pathway to HMRC remains active and correctly configured.

The Decision in Practical Terms

Xero and Sage each offer a credible route to MTD compliance. Xero works best for businesses that want simplicity, automation, and easy external collaboration. Sage works best for businesses that need detailed financial control, high-volume transaction management, or continuity with existing Sage systems.

What both require is correct setup, consistent use, and a clear understanding of what MTD demands from your records. The software provides the infrastructure. Compliance depends on how that infrastructure is built and maintained.


The platform you select shapes how you store records, calculate VAT, and submit returns to HMRC. Two names come up consistently in this conversation: Xero and Sage. Both carry HMRC recognition. Both handle the technical requirements. But they approach the job differently, and understanding those differences is what makes the choice useful rather than arbitrary.

The Baseline: What MTD Demands from Any Software

MTD sets specific technical requirements that software must meet to qualify as compliant.

Your platform must store digital records of all income and expenses. It must calculate VAT automatically from those records. It must generate returns in the format HMRC accepts and transmit them directly via API — not through a manual export or copy-paste process. And it must maintain a complete digital audit trail linking every figure in your return back to the original transaction.

That last point is where many businesses unknowingly fall short. If your process involves transferring numbers from one system into another by hand at any stage, you’ve broken the digital link requirement. The software may be HMRC-approved; the way you’re using it may not be compliant.

Xero and Sage both satisfy these requirements in full. Where they differ is in design philosophy, workflow, and the types of businesses they serve most effectively.

Xero’s Approach to MTD

Xero operates entirely in the cloud. There’s no software to install, no server to maintain, and no files to transfer between devices. You log in through a browser or mobile app, and your data is available in real time to anyone you authorise — including your accountant.

The platform’s MTD-relevant strengths centre on automation. Bank feeds connect directly to your business accounts and pull transactions into Xero automatically. The mobile app lets you photograph receipts and attach them to transactions on the spot. VAT returns are generated from your categorised records with minimal manual input, then submitted to HMRC directly from within the platform.

Xero suits businesses that want to keep day-to-day bookkeeping straightforward. A sole trader, a small consultancy, or a growing e-commerce business will typically find the interface intuitive and the setup manageable without specialist finance knowledge. The accountant collaboration model also works well here — shared access means your adviser can review, adjust, and submit without requiring files to be exported and emailed back and forth.

Sage’s Approach to MTD

Sage has a longer history in UK accounting than most of its competitors, and its user base reflects that. Many established businesses have used Sage products for years, some running operations on Sage 50 or earlier desktop versions.

The modern Sage cloud platform carries forward the structural depth that made those earlier versions popular. Detailed financial ledgers, departmental cost tracking, customisable reporting, and support for multiple VAT schemes give finance teams the granular control they need for complex operations. For businesses processing high transaction volumes or managing accounts across multiple cost centres, that structure is a practical necessity rather than an optional feature.

Sage also offers a defined migration path for businesses moving from legacy desktop versions. Maintaining continuity of financial history — opening balances, VAT records, chart of accounts — matters significantly for businesses with years of data in an existing Sage system. Switching to an entirely new platform means solving a data migration problem that Sage’s own upgrade path avoids.

Matching the Platform to the Business

Neither platform is universally better. The relevant question is which one fits how your business actually operates.

Smaller businesses and sole traders tend to favour Xero. The learning curve is lower, the interface requires less accounting knowledge to navigate, and the automation features reduce the time spent on routine bookkeeping. For businesses without a dedicated finance function, that matters.

Larger businesses and those with internal finance teams often find Sage more capable. Departmental tracking, detailed ledger management, and robust reporting customisation give accountants and finance managers tools they can’t replicate in a simpler platform. Businesses in manufacturing, construction, or other sectors with job costing requirements particularly benefit from Sage’s feature depth.

Transaction volume is another practical consideration. A business processing a handful of invoices per week has different software needs than one handling hundreds of purchase orders and supplier payments daily. Sage’s ledger architecture scales more naturally for the latter.

Both platforms require correct configuration to work as MTD-compliant systems, and that’s where many businesses encounter problems. Selecting the software is straightforward; setting it up correctly is where the detail lies. Services like Xero, QuickBooks & Sage MTD Setup provide structured implementation support, ensuring the platform you choose is configured accurately for HMRC submissions before your first return is due.

What Correct Configuration Actually Involves

Installing software and creating a login is not the same as being MTD-compliant. The configuration work that happens between those two points determines whether your submissions are accurate and whether your records meet HMRC’s digital link requirements.

The VAT scheme selection is one of the most consequential settings. Standard VAT accounting, Cash Accounting, and the Flat Rate Scheme each calculate liability differently. Applying the wrong scheme means every VAT return you produce carries a systematic error — one that may not surface until an HMRC review.

The chart of accounts needs to reflect how your business actually operates, with income and expense categories mapped correctly to the relevant tax treatment. Poorly structured nominal codes produce returns that misrepresent your VAT position, regardless of how carefully you record individual transactions.

The HMRC API connection must be established, authorised, and tested before you file your first return. Bank feeds need to be verified against your actual accounts. For businesses migrating from older systems, historical data must transfer with opening balances and VAT history intact.

Errors at this stage tend to compound. A misconfigured VAT scheme or a misaligned chart of accounts produces incorrect returns quarter after quarter until someone identifies and corrects the underlying problem.

Sustaining Compliance After Implementation

Software configuration is a one-time project, but staying compliant is ongoing. Both Xero and Sage require users who understand how to operate them correctly — logging expenses accurately, reconciling bank feeds regularly, reviewing VAT before submission, and maintaining the categorisation discipline that makes quarterly returns reliable.

Structured onboarding training, tailored to how your business uses the platform, reduces the errors that stem from unfamiliarity. Some businesses also benefit from periodic compliance reviews — a check that records are reconciled, VAT coding is consistent, and the submission pathway to HMRC remains active and correctly configured.

The Decision in Practical Terms

Xero and Sage each offer a credible route to MTD compliance. Xero works best for businesses that want simplicity, automation, and easy external collaboration. Sage works best for businesses that need detailed financial control, high-volume transaction management, or continuity with existing Sage systems.

What both require is correct setup, consistent use, and a clear understanding of what MTD demands from your records. The software provides the infrastructure. Compliance depends on how that infrastructure is built and maintained.

 

New AI Model Improves Personalized Blood Glucose Prediction for Type 1 Diabetes

Jeonbuk National University Researchers Develop an AI Model For Personalized Blood Glucose Monitoring

The hybrid model integrates three components to address key challenges and was rigorously evaluated, paving way for accurate blood glucose prediction

Patients with Type 1 diabetes (T1D) require accurate and consistent monitoring of their blood glucose levels. Over the past decade, AI models have been explored to tackle this challenge; however, inter-patient variability and large data volumes remain key challenges. In a new study, researchers present BiT-MAML, a model-agnostic algorithm aimed at personalized blood glucose prediction of patients with T1D. This approach overcomes the limitations of existing models and enables precise predictions in real clinical settings.

Type 1 diabetes (T1D) is an autoimmune condition in which the body’s own immune system attacks insulin-producing cells. As a result, patients with T1D must closely monitor their blood glucose (BG) levels and rely on insulin injections or pumps. Even small miscalculations or oversights can lead to unregulated blood sugar levels, leading to potentially life-threatening complications.

Continuous glucose monitoring (CGM) systems have emerged as a promising tool for predicting and forecasting BG levels. Over the past decade, researchers have explored artificial intelligence (AI) models for improving the prediction accuracy of CGM systems. However, differences in physiology between patients and poor adaptation for new users persist to challenge the widespread adoption of this technology in real-world settings. In addition, traditional models often focus on either short-term or long-term glucose patterns, but not both.

In an attempt to address these issues, a research team led by Professor Jaehyuk Cho from the Department of Software Engineering at Jeonbuk National University in South Korea, have developed an innovative model, named BiT-MAML, aimed at tackling inter-patient variability in BG prediction. Explaining further, Prof. Cho says, “BG dynamics are not uniform across all patients. The physiological patterns of an elderly patient are vastly different from those of a young adult.” Adding further, he says, “Our model demonstrates how this variability can be accounted for by developing more personalized models.” Their findings were published in Scientific Reports on August 20, 2025. 

BiT-MAML (where “BiT-“ stands for Bidirectional LSTM-Transformer” and “MAML” stands for “Model-Agnostic Meta-Learning”) uses hybrid architecture combining two deep learning models: bidirectional long-short-term memory (Bi-LSTM) and Transformer. Bi-LSTM processes time-series BG data bidirectionally, precisely capturing short-term patterns. Simultaneously, the transformer, utilizing a multi-head attention approach, efficiently models long-term patterns, capturing complex day-to-day and lifestyle-based cyclical variations. During training, the researchers applied a meta-learning approach known as Model-Agnostic Meta-Learning (MAML) that helps the model quickly adapt to new and diverse patients using only a small amount of training data by learning from a wide range of patient examples. 

To test model performance, the researchers adopted a Leave-One-Patient-Out Cross-Validation (LOPO-CV) scheme. “In simple terms, we train the AI on five patients, then test it on the sixth patient it has never seen before,” explains Prof. Cho. “This is effective for assessing the model’s ability to generalize to unseen patients.” 

The model demonstrated significantly reduced prediction error compared to conventional models. Notably, the prediction error varied from an excellent 19.64 milligram/decilitre (mg/dL) for one patient to a challenging 30.57 mg/dL for another. While these results represent a clear improvement over the standard LSTM models, they also highlight the persistent difficulty of managing inter-patient variability in real-world settings. “Our study shows how AI-based BG prediction models should be evaluated to improve both trust and model performance,” concludes Prof. Cho. “Addressing this challenge will contribute to the development of effective CGM models that can serve diverse patients with T1D, from children to elderly.

These findings attest to the fact that the development of effective personalized BG prediction requires the use of advanced AI models incorporating robust evaluation methods that can transparently report the full spectrum of performance.

Reference

Title of original paper: Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model

Journal: Scientific Reports

DOI: 10.1038/s41598-025-13491-5  

Qualcom invests €500K to launch new AI practice

Qualcom, a leading Irish provider of IT and cybersecurity services, today announces that it is investing €500,000 to launch its new artificial intelligence (AI) practice. This investment will span three years and, in the continued expansion of its team, Qualcom plans to hire four AI specialists within this timeframe.

The new practice will support secure AI adoption for Irish organisations and enable them to align with evolving regulatory requirements. The investment includes a new partnership with AI infrastructure provider NROC and, as part of this, Qualcom will provide a full wraparound service to secure and manage customers’ AI environments, using NROC’s technology. The funding also includes the training and upskilling of new team members, as well as AI training for Qualcom’s existing managed services and infosec teams.

In turn, the new practice will further enable Qualcom to deliver AI-powered solutions that will secure customers’ Microsoft data, and to provide ultra-secure managed services to businesses. Qualcom has also developed a comprehensive AI policy framework designed to help organisations to incorporate AI tools such as Microsoft Copilot and ChatGPT into their daily operations, while safeguarding sensitive data and ensuring compliance,

The company is launching the new dedicated practice in response to heightened demand among customers for AI solutions, services, and capabilities to drive business growth and remain competitive.

This investment comes as Qualcom celebrated 30 years in business in 2025. The company recently announced that it has boosted the headcount within its support centre by 33%, and enhanced facilities at its Dublin headquarters to equip the business for continued growth.

David Kinsella, Technical Director, Qualcom, said: “This investment in our people, platforms, and capabilities reflects our commitment to supporting customers as they navigate both the opportunities and risks of AI. As we look ahead to the next three years, there’s no doubt that the use and applications of AI will continue to grow exponentially. The launch of the new practice will enable us to adapt quickly in line with industry demand, delivering right first-time services that are fully compliant and maximise IT uptime for businesses in Ireland. We’re looking forward to working closely with customers as we support the secure rollout of AI tools to help them to keep pace with their competitors.”

Why Penetration Testing Companies Are Essential for Modern Cybersecurity

In a digital economy where data is one of the most valuable assets an organization owns, the ability to detect vulnerabilities before attackers do has become a strategic necessity. Penetration testing companies help organizations uncover hidden security weaknesses by simulating real-world cyberattacks against applications, infrastructure, and networks, allowing businesses to strengthen defenses before malicious actors exploit those gaps.

Why penetration testing has become essential

Cybersecurity threats have grown more sophisticated and persistent in recent years. Enterprises no longer face only opportunistic hackers; they must also defend against organized cybercriminal groups, state-sponsored attackers, and automated attack tools that scan the internet continuously for vulnerabilities.

Traditional security tools—such as firewalls, antivirus software, and intrusion detection systems—play an important role, but they cannot identify every weakness. Many vulnerabilities stem from misconfigurations, insecure code, overlooked access controls, or complex interactions between systems.

Penetration testing addresses this challenge by applying the mindset and techniques of attackers. Security professionals attempt to exploit vulnerabilities in a controlled environment, demonstrating exactly how an attack could unfold and what business impact it might have. Instead of theoretical risks, companies receive practical insight into real security gaps.

What penetration testing companies actually do

Professional penetration testing providers offer a range of services designed to assess different layers of an organization’s technology stack. These services typically include:

Network penetration testing
This type of assessment focuses on internal and external network infrastructure. Testers attempt to exploit weaknesses in routers, servers, firewalls, or network protocols to gain unauthorized access.

Web application testing
Modern organizations rely heavily on web platforms. Penetration testers evaluate applications for vulnerabilities such as SQL injection, cross-site scripting, insecure authentication mechanisms, and flawed session management.

Mobile application security testing
As mobile apps increasingly handle sensitive data and financial transactions, specialized testing ensures they are protected against reverse engineering, insecure APIs, and data leakage.

Cloud security assessments
With many businesses migrating workloads to the cloud, penetration testing helps identify configuration errors, excessive permissions, and exposed services that could allow attackers to move laterally within cloud environments.

Social engineering testing
Some engagements also evaluate human vulnerabilities through phishing simulations or other social engineering techniques. These tests help organizations measure employee awareness and identify training gaps.

The methodology behind effective penetration testing

High-quality penetration testing is structured and systematic rather than random hacking attempts. Professional testers typically follow a standardized methodology that includes several stages.

  1. Reconnaissance and information gathering
    Security specialists collect publicly available information about the target organization, its infrastructure, domains, and technologies. This stage helps testers map potential entry points.
  2. Vulnerability identification
    Automated tools and manual analysis are used to identify weaknesses in software, configurations, and systems.
  3. Exploitation
    Testers attempt to exploit discovered vulnerabilities in order to determine whether they can gain access, escalate privileges, or extract sensitive information.
  4. Post-exploitation analysis
    This phase evaluates how far an attacker could move within the environment after gaining initial access.
  5. Reporting and remediation guidance
    Perhaps the most important stage is the final report, which includes detailed findings, severity ratings, proof-of-concept evidence, and clear recommendations for remediation.

The goal is not only to expose vulnerabilities but also to provide organizations with actionable guidance to improve their overall security posture.

How businesses benefit from penetration testing

Organizations that invest in regular penetration testing gain several advantages beyond simple vulnerability detection.

First, testing helps reduce the risk of costly data breaches. A single cyber incident can lead to financial losses, regulatory penalties, operational disruption, and reputational damage.

Second, penetration testing supports regulatory compliance. Many industries—including finance, healthcare, and e-commerce—require periodic security assessments to meet standards such as PCI DSS, ISO 27001, or HIPAA.

Third, it improves internal security maturity. When development and infrastructure teams receive detailed feedback from testers, they gain a deeper understanding of secure architecture and coding practices.

Finally, penetration testing strengthens customer trust. Demonstrating that systems are regularly tested by independent experts signals a strong commitment to protecting user data.

Choosing the right penetration testing partner

Not all security providers deliver the same level of expertise or value. When selecting a penetration testing company, organizations should consider several factors.

Technical expertise is critical. Experienced testers should hold recognized certifications such as OSCP, CEH, or CREST, and have proven experience with modern technologies including cloud platforms, APIs, and containerized environments.

Methodology and transparency also matter. Reputable firms clearly explain their testing process, scope, and reporting structure before the engagement begins.

Industry experience can significantly improve the quality of testing. Providers familiar with sectors like fintech, healthcare, or logistics understand common threat patterns and regulatory expectations.

Actionable reporting is another key factor. Security reports should translate technical findings into clear business risks and remediation steps that engineering teams can realistically implement.

The growing role of penetration testing in modern cybersecurity

As digital ecosystems expand, the attack surface of organizations grows with them. Cloud services, APIs, IoT devices, and remote work infrastructure all introduce new potential entry points for attackers.

Because of this complexity, cybersecurity can no longer rely solely on defensive monitoring tools. Businesses must proactively search for weaknesses in the same way adversaries do. Regular penetration testing has therefore evolved from a niche security service into a core component of modern cyber risk management.

Organizations that integrate testing into their security lifecycle—especially during software development and infrastructure changes—can detect vulnerabilities earlier and reduce remediation costs significantly.

In this environment, companies increasingly turn to specialized security partners to strengthen their defenses. Andersen penetration testing company services, for example, are often integrated into broader cybersecurity and software engineering initiatives, enabling businesses to identify vulnerabilities early, validate the resilience of their systems, and continuously improve their security posture as their digital products evolve.

How Live Entertainment Technology Is Changing Traditional Table Games

If you’ve spent any time wandering through the quiet, prestigious streets of Mayfair, you know that the atmosphere of a high-end gaming room is nearly impossible to bottle. It’s the sound of a shuffled deck, the weighted click of a chip, and that unspoken nod between a dealer and a regular. For a long time, the digital world simply couldn’t compete with that. But things have shifted. We’ve moved far beyond the clunky, cartoonish graphics of the early internet. Today, the tech driving live entertainment is doing something quite remarkable: it’s making the screen disappear.

While 4K streaming is certainly a treat for the eyes, the most significant change isn’t found in pixel counts alone—it’s in the depth of the immersion. With the integration of Augmented Reality (AR), you’re no longer just looking at a video feed of a table. You’re seeing digital overlays that track every card movement and betting pattern in real-time. It’s a bit surreal, honestly. You might be sitting on your sofa, but the visual data makes the game feel more transparent than ever.

Bridging the Gap to the Physical Floor

I’ve often wondered if a digital interface could ever truly replicate the “soul” of a physical club. Interestingly, advances in live dealer casino technology are often compared to the experience offered in physical venues across Mayfair, specifically in how they prioritize the human element. The dealers aren’t just there to flip cards; they are trained entertainers and facilitators.

High-speed, low-latency 5G has been the real hero here. Without it, the “live” part of the experience would be a stuttering mess. Now, the interaction is instantaneous. When you ask a question or place a late bet, the response is immediate. This lack of lag creates a kind of psychological bridge. Before you know it, your brain stops treating the screen like a “game” and starts treating the whole thing like a genuine event. It’s a strange shift. This seamlessness happens because of several layers of tech humming away in the background—stuff you’d never notice unless it broke.

Take Optical Camera Recognition, for instance. It’s basically the “eyes” of the operation, instantly translating a physical card shuffle into digital data. Then you have the cinematography. It isn’t just a static webcam anymore; automated cameras now pivot and zoom based on where the action is, much like how your own eyes would dart around a table in a real room. Some setups are even experimenting with haptic feedback, where your phone gives a tiny, tactile buzz to mimic the vibration of a roulette ball hitting the pocket. It sounds small, but those little touches really pull you in.

Why It Matters Beyond the Fun

It isn’t all just bells and whistles, though. I’ve noticed that as the tech gets more sophisticated, the people running the show have to be more responsible, too. It’s a bit of a double-edged sword. There’s a lot of talk about how AI monitors these games now. While that sounds a bit “Big Brother,” it’s actually there to spot patterns of risky behavior that a human eye might miss. I think it’s a positive step.

It’s how regulations drive responsible online casino gaming that really defines the current era. By using data to ensure players are staying within their limits, the industry is trying to prove it can be both high-tech and high-standard. It’s about longevity, not just a quick thrill.

What do you think about this digital shift? Does the convenience of a high-tech live stream ever truly beat the feeling of a night out in a classic London venue, or is the technology finally getting close enough to call it a draw? I’d love to hear your thoughts on whether you prefer the haptic buzz of a phone or the weight of a premium gaming chip.

 

How Smart Vehicle Technology and Real Time Data Are Reshaping Road Safety and Driver Accountability

Modern vehicles are no longer isolated mechanical machines. They operate as connected platforms equipped with sensors, software, and communication tools that collect and process real time data. Automakers now integrate advanced driver assistance systems, onboard diagnostics, and cloud connectivity to enhance safety and performance. These technologies actively monitor speed, braking patterns, lane positioning, and surrounding traffic conditions to reduce human error and support informed driving decisions.

This transformation reflects a broader shift within the mobility sector. Vehicles now function as part of a digital ecosystem that includes mobile applications, traffic infrastructure, and telematics services. Real time data exchange allows drivers to receive alerts, optimize routes, and respond to road hazards more efficiently. As this technology becomes standard rather than optional, it shapes expectations around safety, transparency, and accountability on the road.

Manufacturers also collaborate with software developers and telecommunications providers to strengthen connectivity reliability. Over the air updates improve system performance without requiring physical servicing, while cloud platforms store anonymized performance data to refine future safety features. This continuous improvement cycle ensures that vehicles evolve long after purchase. As hardware and software operate together, connected mobility systems create an environment where prevention and informed response replace reactive measures.

Technology and Accountability After a Road Collision

According to www.accidentjusticepro.com, a car accident is not only a moment of physical impact. It triggers insurance claims, liability assessments, potential legal action, and safety reviews that can extend for months. Traditionally, fault determination relied heavily on eyewitness accounts, physical damage inspection, and police reports. These methods often produced conflicting narratives, especially in complex multi vehicle collisions. Today, connected vehicle systems and digital recording tools provide a structured layer of evidence that reshapes how a car accident is evaluated from both legal and technical perspectives.

When a car accident occurs, event data recorders capture pre impact speed, braking input, seatbelt usage, airbag deployment timing, and steering direction. Telematics systems log GPS positioning and vehicle behavior in real time. This information can confirm whether a driver attempted evasive action, exceeded speed limits, or ignored automated safety warnings. Insurance providers and legal professionals increasingly rely on this data to resolve disputes more efficiently. While the collision itself remains a serious and often disruptive event, technology reduces ambiguity in its aftermath and introduces measurable accountability into what was once largely subjective analysis.

Artificial Intelligence in Risk Detection

Artificial intelligence has expanded the capabilities of vehicle safety systems. Advanced algorithms analyze patterns from millions of driving scenarios to detect potential risks in real time. Lane departure warnings, adaptive cruise control, automatic emergency braking, and pedestrian detection systems operate by interpreting sensor inputs within fractions of a second. These features reduce reaction time gaps that often contribute to roadway incidents.

Beyond in vehicle systems, AI also supports traffic management platforms. Cities deploy smart traffic signals and predictive analytics to monitor congestion and adjust flow dynamically. This broader infrastructure integration reduces bottlenecks and high risk intersections. By combining vehicle intelligence with smart city frameworks, the transportation ecosystem becomes more responsive and data driven, contributing to safer road environments overall.

Machine learning models continue to improve as they process larger volumes of driving data. Developers refine algorithms to account for diverse weather conditions, road surfaces, and traffic behaviors. As a result, safety systems adapt more effectively to real world variability. Continuous algorithm training strengthens predictive accuracy and enhances driver assistance reliability without increasing complexity for the user.

Telematics and Behavioral Insights

Telematics systems collect ongoing driving data, including acceleration patterns, braking intensity, and cornering behavior. Fleet operators and insurers use this information to evaluate driving performance and encourage responsible habits. Drivers receive feedback through mobile dashboards, allowing them to identify areas for improvement and reduce risky behaviors over time.

This data driven approach promotes accountability without constant supervision. Rather than relying solely on post incident assessments, telematics shifts attention toward prevention. Businesses that manage vehicle fleets benefit from reduced operational risks, while individual drivers gain greater awareness of how their habits influence safety outcomes. The growing adoption of telematics reflects the broader digital transformation within transportation technology.

Behavioral analytics platforms also support customized training initiatives. Organizations can identify consistent risk indicators and design targeted coaching programs to address them. Over time, this structured feedback loop encourages measurable improvement in driving standards. Telematics therefore functions not only as a monitoring tool but also as a practical mechanism for long term risk reduction and performance enhancement.

Cybersecurity and Data Integrity in Modern Vehicles

As vehicles become increasingly connected, cybersecurity becomes a critical priority. Protecting sensitive driving data and preventing unauthorized system access is essential to maintain trust in digital mobility platforms. Manufacturers invest in encryption protocols, secure software updates, and network monitoring to reduce vulnerabilities. Without strong safeguards, connected systems could expose drivers to privacy risks or operational disruptions.

Data integrity also affects accountability. Accurate records must remain tamper resistant to ensure fairness in assessments and investigations. Reliable cybersecurity frameworks support the legitimacy of digital evidence and protect both drivers and service providers. As connected vehicles continue to evolve, maintaining robust security standards remains central to sustaining confidence in smart transportation technologies.

Security architecture now incorporates multi layer defenses that isolate critical vehicle functions from external communication channels. Regular penetration testing and vulnerability assessments strengthen system resilience against emerging threats. By embedding security principles into design rather than treating them as afterthoughts, manufacturers protect both operational stability and data credibility. This proactive approach reinforces trust in connected vehicle ecosystems.

A New Standard for Road Responsibility

The integration of smart vehicle systems, real time analytics, and connected infrastructure has redefined how responsibility is evaluated on the road. Decisions are no longer based solely on testimony or fragmented observations. Instead, comprehensive datasets provide structured insight into driving behavior and vehicle performance. This shift supports more objective evaluations and encourages higher safety standards across the mobility sector.

Looking ahead, continued innovation in sensor technology, AI modeling, and infrastructure connectivity will further refine how road incidents are prevented and assessed. As technology advances, drivers, manufacturers, insurers, and regulators must collaborate to balance innovation with ethical data practices. Smart mobility systems are not simply convenience features. They represent a structural change in how road safety and accountability are approached in a digitally connected world.

As adoption expands, expectations around transparency and measurable responsibility will continue to rise. Stakeholders across the transportation industry will rely more heavily on verified digital records and predictive systems to guide policy and operational standards. The result is a mobility landscape shaped by data driven evaluation and continuous improvement. Smart vehicle technology has established a durable framework that reshapes how safety, performance, and accountability coexist on modern roads.

 

Dell PowerEdge XR9700 Brings Cloud RAN and AI to Harsh Edge Environments

Dell Technologies introduces the Dell PowerEdge XR9700 server, a first of its kind closed-loop liquid-cooled, fully-enclosed, ruggedized server engineered to run Cloud RAN and edge AI workloads in unprotected outdoor environments. Designed to mount on utility poles, rooftops and building exteriors, the PowerEdge XR9700 brings high performance computing into dense urban areas, remote locations, and space-constrained facilities where traditional data center infrastructure cannot reach.

Why it matters

Telecommunications operators and those working at the edge often struggle to deploy compute due to lack of power and space. The PowerEdge XR9700 solves this, delivering high performance compute directly at the point of need in an ultra-compact, zero-footprint IP66-rated enclosure that’s sealed from the elements. For telecommunications operators, it provides a flexible, software-defined alternative to traditional RAN solutions, supporting Cloud RAN and Open RAN processing at the cell site. At the same time, the platform can run edge and AI applications directly where data is created and consumed.

Built for Extreme Conditions

Designed to withstand the harshest environments, this platform’s ultra-compact IP66-rated enclosure and GR-3108 Class 4 certification delivers reliable, quiet performance in environments exposed to extreme temperatures, dust and moisture. Closed-loop liquid cooling with a thermal management architecture maintains consistent operation across a temperature range of -40°C to 46°C (-40°F to 115°F) and withstands direct solar radiation, all in a compact 15-liter form factor suitable for mounting on utility poles, rooftops and building sides. This zero-footprint design brings telecom and edge workloads to locations where only traditional radio solutions could previously operate.

Performance that Scales

Powered by the Intel Xeon 6 SoC with integrated Intel vRAN Boost technology and Intel AMX technology, the PowerEdge XR9700 delivers the processing power and fronthaul connectivity to support up to 15 5G sectors in a single server. While optimized for Cloud RAN, the platform’s flexibility allows operators to run edge and AI workloads based on network architecture and service requirements.

As part of the Dell PowerEdge XR-Series, the XR9700 integrates with Dell’s existing management tools and software stack. Integrated Dell Remote Access Controller (iDRAC) provides remote visibility and control for zero-touch provisioning (ZTP), while compatibility with the same Cloud RAN software validated on the PowerEdge XR8720t simplifies certification and accelerates telecom deployments.

Andrew Vaz, vice president, Dell Technologies“Operators and enterprises shouldn’t have to compromise when deploying compute in challenging environments. The Dell PowerEdge XR9700 brings Cloud RAN, Open RAN, and edge AI capabilities to places they’ve never been able to go before, opening up new possibilities for network expansion and edge applications.”

 Availability

The Dell PowerEdge XR9700 will be globally available 2H CY 2026.

Additional resources

  • Find out more about the Dell PowerEdge XR9700.
  • Learn more about Dell Open Telecom Ecosystem Lab (OTEL) AI-assisted telecom testing and validation.
  • Connect with Dell on X and LinkedIn

About Dell Technologies
Dell Technologies (NYSE: DELL) helps organizations and individuals build their digital future and transform how they work, live and play. The company provides customers with the industry’s broadest and most innovative technology and services portfolio for the AI era.